---
title: MultiAgent Research Assistant
emoji: 💬
colorFrom: yellow
colorTo: purple
sdk: gradio
sdk_version: 5.0.1
app_file: app.py
pinned: true
license: apache-2.0
short_description: A MultiAgent research assistant and critique
tags:
  - agent-demo-track
---



Multi-Agent Research Assistant
A powerful research assistant built using LangChain agents, LangGraph, and Hugging Face Transformers, designed to automate the research process across academic topics. This app retrieves papers, summarizes them, critiques findings, and generates a final synthesized report—all via coordinated AI agents.

🚀 Demo (Hugging Face Space)

Enter your research topic and let the assistant do the heavy lifting.

🧩 Agents Overview
Agent	Description
Retriever	Queries ArXiv, Semantic Scholar, OpenAlex for relevant academic papers.
Summarizer	Extracts core ideas and results from each paper using Mistral-small.
Critique	Compares papers, detects contradictions, and flags hype/missing data.
Synthesizer	Generates a final report with structured summary and analysis.

🛠️ Tech Stack
LangChain for agent orchestration

Mistral models (Tiny, Small, Medium, Large) via Hugging Face Inference APIs

FAISS for optional RAG (Retrieval-Augmented Generation)

PDFPlumber for extracting full-text content

Research APIs: ArXiv, Semantic Scholar, OpenAlex, PapersWithCode

Gradio UI for simple user interaction












An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).